pandas hierarchical index slicing based on year index

Question

I have a dataset, data1. I am trying to use indexing slicing based on input

where data1 =

                  stats
gender  year    
        
women   2003    cellphone use
        2007    height
        2007    cigarette use
        2008    weight
        2009    cellphone use
        2015    cigarette use
        2018    weight
        2020    height

Here is my attempt at index slicing:

 isvalid_yr = False
 while not isvalid_yr:
     year_input = int(input("Input the year you want to compare data from: "))
     if year_input in data1.index.get_level_values('year') 
         idx = pd.IndexSlice
         isvalid_yr = True
         new_data1 = data1.loc(axis = 0)[idx[year_input:year_input], idx[:]]
     else:
          isvalid_yr = False
     try:
         if isvalid_yr ==True:
             pass
         else:
             raise ValueError("Year not in data!")
         except ValueError as err:
             print("Year not in data!")

It gives me this output which I do not want.

Empty DataFrame
Columns: [stats]
Index: []

my final desired output that I want to achieve would look like this

Input the year you want to compare data from: 2007

result of new_data1 =

                  stats
gender  year    

women   
        2007    height
        2007    cigarette use

Answer 1

Use xs to grab a cross-section of the DataFrame:

res = df.xs(2007, axis=0, level='year', drop_level=False)

res:

                     stats
gender year               
women  2007         height
       2007  cigarette use

With user input:

while True:
    try:
        year_input = int(
            input("Input the year you want to compare data from: ")
        )
        res = df.xs(year_input, axis=0, level='year', drop_level=False)
        break
    except KeyError:
        print("Year not in data!")
    except ValueError:
        print("Please enter a valid year")

---

df used:

df = pd.DataFrame({
    'gender': ['women', 'women', 'women', 'women', 'women', 'women', 'women',
               'women'],
    'year': [2003, 2007, 2007, 2008, 2009, 2015, 2018, 2020],
    'stats': ['cellphone use', 'height', 'cigarette use', 'weight',
              'cellphone use', 'cigarette use', 'weight', 'height']
}).set_index(['gender', 'year'])

df:

                     stats
gender year               
women  2003  cellphone use
       2007         height
       2007  cigarette use
       2008         weight
       2009  cellphone use
       2015  cigarette use
       2018         weight
       2020         height